1. Field of the Invention
The present invention relates to apparatus for and method of diagnosing damage (or defect) factor of machinery or equipment, which is capable of accurately diagnosing a machinery damage factor for, for example, turbine rotors and generators during an operation for a short time, and the machinery damage factor for the turbine rotor may include vibration factor, shifting in location position, leak noise of steam, etc.
2. Related Art
For example, turbines such as a steam turbine, a gas turbine or a combined cycle turbine combining them have been applied to a power generation plant. In these turbines, for example, in the steam turbine, when failure occurs during the operation, but the failure is not overlooked without being found, there is a possibility that enormous accidents happen. In fact, some failures have been known and found.
In the steam turbine, the following factors for causing the failure are given.
That is, there are given: (1) poor aligning of turbine rotor (rotary shaft) and bearing; (2) rubbing noise (contact noise of turbine rotor with labyrinth packing); (3) eccentricity of turbine rotor and bearing; (4) lubrication failure due to shortage of lubricating oil; and (5) scratches on the surface of the turbine rotor and bearing internal surface, for example, shaft vibration is always monitored so as to collect data, and diagnosis is performed based on the collected data. In FIG. 10, there is shown a conventional vibration diagnosis apparatus having the configuration described above.
As seen from FIG. 10, a system load 1 is connected to a high-pressure turbine HP, a low-pressure turbine LP and a generator G coaxially combined with the low-pressure turbine via a circuit switch 2.
When the turbine starts or stops, a turning gear device 3 for turning (rotating) the turbine (at low speed) is connected directly to the shaft of a turbine rotor 4.
The shaft end of the high-pressure turbine HP is provided with a speed detector 5. The rotational speed of the turbine is converted into an electrical signal, and thereafter, is inputted to a failure (abnormality) diagnosis apparatus 6.
In the illustrated example, the turbine rotor 4 is provided with a vibration detector 5a for detecting vibration as one of machinery damage (damaging or damaged) factors. The detected signal is inputted to the failure diagnosis apparatus 6.
Each bearing of the turbine is provided with rub check detectors 7a, 7b, 7c, 7d and temperature detectors 8a, 8b, 8c, 8d for detecting a return oil temperature of the bearing. Further, each bearing of the turbine is attached with an ampere meter 10 for detecting a current of a motor for driving a turning gear. These above detectors 7a, 7b, 7c, 7d, 8a, 8b, 8c, 8d and 10 then generate signals, which are inputted to the failure diagnosis apparatus 6.
The failure diagnosis apparatus 6 includes an input processor 11 and a timer 12. The input processor 11 inputs turbine rotational speed and signals from the above vibration detector 5a, valve lift detector 17 of a steam valve (steam governing valve) 16, vibration detector, rub check detectors 7a, 7b, 7c, 7d, temperature detectors 8a, 8b, 8c, 8d and ampere meter 10 as input data. Further, the failure diagnosis apparatus 6 includes a memory 13, a controller 14 and a display device 15. The memory 13 receives the outputs of the input processor 11 and the timer 12 and receives speed reducing data in preset failure diagnosis and in a normal mode under the same condition and return oil temperature data of bearings during the operation of the turbine. The controller 14 acts to determine the failure (abnormality) based on the output from the memory 13. The display device 15 acts to display the failure thus determined, in addition to above matters. When steam ST is flowing through the steam valve 16, high-pressure turbine HP, low-pressure turbine LP and condenser 18, if any failure event happens, the turbine is stopped in response to the failure so as to prevent enormous accidents.
In the conventional steam turbine, for example, at a time when diagnosing shaft vibration, vibration generation events, vibration waveforms and the magnitude of waveform amplitude are calculated based on the above detection data. Thereafter, the vibration generation factor is estimated from the thus calculated data based on knowledge and experience of the diagnosis responsible (judgment) person. In this manner, suitable courses to be taken against the generation factor obtained from the above estimation have been prepared as vibration guidance.
However, the accuracy of the vibration generation factor thus estimated almost depends on a grade of vibration knowledge of a person, who diagnoses vibration.
For instance, if remarkably high unstable vibration is estimated from a natural frequency of a turbine rotor, the following factors of generating the above unstable vibration are considered. One is unstable vibration by an oil pump resulting from the oil film strength of lubricating oil of bearings or the shortage of lubricating oil of bearings. Another is unstable vibration resulting from steam vibrating the turbine. In order to specify the generated vibration and investigate the generation factor, the turbine operation mode and condition at a time when vibration generates is investigated in addition to the vibration waveform features at a time when vibration generates. Thereafter, the true generation factor has been found in collation with the vibration knowledge and experience rule.
For this reason, the following problem arises. Depending on the ability of a person (diagnosis responsible person), who is in charge of vibration diagnosis, remarkable difference appears in accuracy of vibration diagnosis result, probability and time spent until the diagnosis result is made. Thus, newly advanced improvement is required that all persons can accurately and relatively readily make diagnosis for a short time if they have common knowledge.